-------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /accounts/grad/haowen.wu/Documents/EJR-revise/dynamic/check_May201
> 9/mlogit-full-before-Aug2017.log
  log type:  text
 opened on:  25 May 2019, 21:04:51

. model_transition,job(0)
From Purely Professional

Iteration 0:   log pseudolikelihood = -526658.78  
Iteration 1:   log pseudolikelihood = -445172.12  
Iteration 2:   log pseudolikelihood = -437501.06  
Iteration 3:   log pseudolikelihood = -437318.16  
Iteration 4:   log pseudolikelihood = -437317.41  
Iteration 5:   log pseudolikelihood = -437317.41  

Multinomial logistic regression                 Number of obs     =    559,786
                                                Wald chi2(94)     =  211005.08
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -437317.41               Pseudo R2         =     0.1696

                         (Std. Err. adjusted for 97,427 clusters in title_id1)
------------------------------------------------------------------------------
             |               Robust
  transition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
1            |
  female_lag |
          0  |    -.32405   .0426025    -7.61   0.000    -.4075494   -.2405507
          1  |  -.3409298    .097091    -3.51   0.000    -.5312246    -.150635
             |
title_female |
          0  |  -.0285062   .0117169    -2.43   0.015    -.0514709   -.0055414
          1  |  -.0302077   .0268978    -1.12   0.261    -.0829265     .022511
             |
  female_lag#|
title_female |
        0 0  |   .0463759   .0215386     2.15   0.031      .004161    .0885909
        0 1  |  -.0281243   .0594478    -0.47   0.636      -.14464    .0883913
        1 0  |  -.0590357   .0669342    -0.88   0.378    -.1902243     .072153
        1 1  |   .0629282    .053003     1.19   0.235    -.0409557    .1668121
             |
0.title_p_~y |  -.0036468   .0082075    -0.44   0.657    -.0197332    .0124396
             |
  female_lag#|
title_p_ac~y |
        0 0  |  -.0153754   .0185703    -0.83   0.408    -.0517725    .0210216
        1 0  |   .0125595   .0416774     0.30   0.763    -.0691268    .0942457
             |
1.title_pe~y |  -.0592874   .0178051    -3.33   0.001    -.0941848   -.0243901
             |
  female_lag#|
title_pers~y |
        0 1  |  -.0126903   .0411304    -0.31   0.758    -.0933044    .0679238
        1 1  |   .0535036   .0649615     0.82   0.410    -.0738186    .1808259
             |
first_female |
          0  |  -.0226895   .0083291    -2.72   0.006    -.0390142   -.0063648
          1  |   -.067753     .01878    -3.61   0.000    -.1045611   -.0309449
             |
  female_lag#|
first_female |
        0 0  |   .0194069   .0185717     1.04   0.296    -.0169931    .0558068
        0 1  |   .1253989   .0481108     2.61   0.009     .0311035    .2196943
        1 0  |   .0214263    .054827     0.39   0.696    -.0860327    .1288852
        1 1  |   .1148453   .0493937     2.33   0.020     .0180354    .2116553
             |
0.first_p_~y |   .3719884   .0083594    44.50   0.000     .3556042    .3883725
             |
  female_lag#|
first_p_ac~y |
        0 0  |   .1133488   .0207962     5.45   0.000      .072589    .1541086
        1 0  |   .1474215   .0485347     3.04   0.002     .0522953    .2425478
             |
1.first_pe~y |  -.1856235   .0118903   -15.61   0.000    -.2089281    -.162319
             |
  female_lag#|
first_pers~y |
        0 1  |  -.1034529   .0288333    -3.59   0.000    -.1599652   -.0469407
        1 1  |  -.0397143   .0582589    -0.68   0.495    -.1538996     .074471
             |
group_p_ac~y |   6.068716    .022305   272.08   0.000     6.024998    6.112433
             |
  female_lag#|
          c. |
group_p_ac~y |
          0  |   .2445102   .0525846     4.65   0.000     .1414463    .3475741
          1  |   .2765779   .1205709     2.29   0.022     .0402634    .5128924
             |
group_pers~y |   3.265749   .0435906    74.92   0.000     3.180313    3.351185
             |
  female_lag#|
          c. |
group_pers~y |
          0  |   .2222455   .1013214     2.19   0.028     .0236592    .4208318
          1  |  -.4326106   .1881225    -2.30   0.021     -.801324   -.0638972
             |
job_rank_lag |
          1  |   .0577549   .0175015     3.30   0.001     .0234525    .0920573
          2  |   .0051585   .0170915     0.30   0.763    -.0283402    .0386572
          3  |    .030531   .0214818     1.42   0.155    -.0115727    .0726346
          4  |  -.0796279   .0405329    -1.96   0.049     -.159071   -.0001848
             |
  female_lag#|
job_rank_lag |
        0 1  |  -.0205403   .0355788    -0.58   0.564    -.0902735    .0491929
        0 2  |  -.0053168   .0377133    -0.14   0.888    -.0792336       .0686
        0 3  |   .0083896   .0406408     0.21   0.836     -.071265    .0880441
        0 4  |    .081274   .0482639     1.68   0.092    -.0133216    .1758696
        1 1  |  -.0333016   .0765728    -0.43   0.664    -.1833816    .1167784
        1 2  |  -.0405244   .0772153    -0.52   0.600    -.1918636    .1108147
        1 3  |  -.1280783   .0811585    -1.58   0.115     -.287146    .0309893
        1 4  |   .0081268   .0921722     0.09   0.930    -.1725273    .1887809
             |
    ln_post2 |   .1425406   .0038694    36.84   0.000     .1349567    .1501246
             |
  female_lag#|
  c.ln_post2 |
          0  |   .0460959   .0080802     5.70   0.000     .0302589    .0619329
          1  |   .0171448   .0187184     0.92   0.360    -.0195425    .0538322
             |
       _cons |  -3.592847   .0184551  -194.68   0.000    -3.629018   -3.556675
-------------+----------------------------------------------------------------
2            |
  female_lag |
          0  |  -.1076726   .0720882    -1.49   0.135    -.2489628    .0336176
          1  |    .832198   .1290594     6.45   0.000     .5792463     1.08515
             |
title_female |
          0  |  -.0268173   .0193413    -1.39   0.166    -.0647256     .011091
          1  |   -.116247   .0385844    -3.01   0.003     -.191871   -.0406229
             |
  female_lag#|
title_female |
        0 0  |   .0203851     .03452     0.59   0.555    -.0472728     .088043
        0 1  |  -.0412494   .0797058    -0.52   0.605    -.1974698    .1149711
        1 0  |    .020665   .0821577     0.25   0.801    -.1403611    .1816911
        1 1  |   .2284269   .0660274     3.46   0.001     .0990155    .3578383
             |
0.title_p_~y |   .0295761   .0133575     2.21   0.027     .0033959    .0557562
             |
  female_lag#|
title_p_ac~y |
        0 0  |  -.0269466   .0295505    -0.91   0.362    -.0848644    .0309712
        1 0  |  -.0410296   .0533534    -0.77   0.442    -.1456004    .0635411
             |
1.title_pe~y |  -.2689771   .0260202   -10.34   0.000    -.3199757   -.2179785
             |
  female_lag#|
title_pers~y |
        0 1  |  -.0193547   .0574357    -0.34   0.736    -.1319266    .0932172
        1 1  |    .141702   .0729759     1.94   0.052    -.0013281     .284732
             |
first_female |
          0  |  -.0001553   .0138592    -0.01   0.991    -.0273189    .0270083
          1  |  -.0858754   .0282073    -3.04   0.002    -.1411608   -.0305901
             |
  female_lag#|
first_female |
        0 0  |  -.0316502   .0300469    -1.05   0.292    -.0905411    .0272407
        0 1  |  -.0054627   .0678707    -0.08   0.936    -.1384867    .1275614
        1 0  |  -.0702558   .0692096    -1.02   0.310    -.2059041    .0653925
        1 1  |  -.0363913   .0646792    -0.56   0.574    -.1631602    .0903776
             |
0.first_p_~y |   .2102391   .0139228    15.10   0.000     .1829509    .2375273
             |
  female_lag#|
first_p_ac~y |
        0 0  |   .0554356   .0334312     1.66   0.097    -.0100883    .1209596
        1 0  |  -.0127904   .0631303    -0.20   0.839    -.1365236    .1109428
             |
1.first_pe~y |  -.6955693   .0191655   -36.29   0.000    -.7331331   -.6580056
             |
  female_lag#|
first_pers~y |
        0 1  |  -.0746181   .0439887    -1.70   0.090    -.1608344    .0115983
        1 1  |   .1705045    .071277     2.39   0.017     .0308042    .3102047
             |
group_p_ac~y |   3.343718   .0389306    85.89   0.000     3.267416    3.420021
             |
  female_lag#|
          c. |
group_p_ac~y |
          0  |  -.0080557   .0896202    -0.09   0.928    -.1837081    .1675968
          1  |  -.5313412   .1671482    -3.18   0.001    -.8589457   -.2037366
             |
group_pers~y |   11.06834   .0637012   173.75   0.000     10.94349    11.19319
             |
  female_lag#|
          c. |
group_pers~y |
          0  |   .2259089   .1357379     1.66   0.096    -.0401326    .4919504
          1  |  -2.534885   .2052995   -12.35   0.000    -2.937265   -2.132506
             |
job_rank_lag |
          1  |   .0147098   .0273808     0.54   0.591    -.0389557    .0683752
          2  |  -.0514675   .0292026    -1.76   0.078    -.1087035    .0057684
          3  |   .0347726   .0339904     1.02   0.306    -.0318474    .1013926
          4  |  -.2367301   .0728053    -3.25   0.001    -.3794258   -.0940344
             |
  female_lag#|
job_rank_lag |
        0 1  |   .0485194   .0570864     0.85   0.395     -.063368    .1604067
        0 2  |   .0783237   .0636749     1.23   0.219    -.0464768    .2031241
        0 3  |    .103494   .0647132     1.60   0.110    -.0233416    .2303295
        0 4  |   .2426474   .0861696     2.82   0.005     .0737582    .4115367
        1 1  |  -.0349389   .1024041    -0.34   0.733    -.2356473    .1657694
        1 2  |  -.0791893   .1192967    -0.66   0.507    -.3130067     .154628
        1 3  |  -.0252716   .1169946    -0.22   0.829    -.2545768    .2040336
        1 4  |   .1391512   .1408984     0.99   0.323    -.1370046     .415307
             |
    ln_post2 |    .221581   .0059854    37.02   0.000     .2098499    .2333122
             |
  female_lag#|
  c.ln_post2 |
          0  |   .0314756   .0125411     2.51   0.012     .0068954    .0560557
          1  |  -.0592157   .0238926    -2.48   0.013    -.1060444    -.012387
             |
       _cons |  -4.772393   .0323194  -147.66   0.000    -4.835737   -4.709048
-------------+----------------------------------------------------------------
3            |  (base outcome)
------------------------------------------------------------------------------
average ME

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |  -.0063891   .0015652    -4.08   0.000    -.0094568   -.0033214
          2  |   .0005738    .001039     0.55   0.581    -.0014625    .0026101
          3  |   .0058153   .0015113     3.85   0.000     .0028533    .0087773
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0289411   .0044451    -6.51   0.000    -.0376534   -.0202289
          2  |   .0103718   .0026815     3.87   0.000     .0051162    .0156273
          3  |   .0185694   .0041928     4.43   0.000     .0103517    .0267871
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

scalars:
                 r(r1) =  .6931471824645996
                 r(r2) =  1.098612308502197
                 r(r3) =  1.609437942504883
                 r(r4) =  1.791759490966797
                 r(r5) =  2.079441547393799
                 r(r6) =  2.397895336151123
                 r(r7) =  2.56494927406311
                 r(r8) =  2.833213329315186
                 r(r9) =  3.135494232177734

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))

1._at        : ln_post2        =           0

2._at        : ln_post2        =    .6931472

3._at        : ln_post2        =    1.098612

4._at        : ln_post2        =    1.609438

5._at        : ln_post2        =    1.791759

6._at        : ln_post2        =    2.079442

7._at        : ln_post2        =    2.397895

8._at        : ln_post2        =    2.564949

9._at        : ln_post2        =    2.833213

10._at       : ln_post2        =    3.135494

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
_predict#_at |
       1  1  |   -.022223   .0033833    -6.57   0.000    -.0288541   -.0155919
       1  2  |  -.0165393   .0025123    -6.58   0.000    -.0214633   -.0116154
       1  3  |  -.0132879    .002078    -6.39   0.000    -.0173608    -.009215
       1  4  |  -.0092872   .0016863    -5.51   0.000    -.0125923   -.0059822
       1  5  |  -.0078883   .0016096    -4.90   0.000    -.0110431   -.0047335
       1  6  |  -.0057148   .0015743    -3.63   0.000    -.0088004   -.0026292
       1  7  |  -.0033598   .0016599    -2.02   0.043    -.0066131   -.0001064
       1  8  |  -.0021469   .0017511    -1.23   0.220    -.0055789    .0012851
       1  9  |   -.000233   .0019495    -0.12   0.905    -.0040539    .0035879
       1 10  |    .001872   .0022293     0.84   0.401    -.0024974    .0062414
       2  1  |  -.0005669   .0018381    -0.31   0.758    -.0041695    .0030356
       2  2  |  -.0001128   .0014842    -0.08   0.939    -.0030218    .0027962
       2  3  |   .0001366   .0012865     0.11   0.915     -.002385    .0026581
       2  4  |   .0004272   .0010937     0.39   0.696    -.0017165    .0025709
       2  5  |   .0005234   .0010547     0.50   0.620    -.0015437    .0025905
       2  6  |    .000666   .0010409     0.64   0.522    -.0013742    .0027061
       2  7  |   .0008093   .0011053     0.73   0.464    -.0013571    .0029757
       2  8  |   .0008779   .0011728     0.75   0.454    -.0014207    .0031765
       2  9  |   .0009778   .0013242     0.74   0.460    -.0016175    .0035731
       2 10  |   .0010741   .0015474     0.69   0.488    -.0019587     .004107
       3  1  |     .02279   .0034745     6.56   0.000     .0159802    .0295998
       3  2  |   .0166521   .0025302     6.58   0.000      .011693    .0216112
       3  3  |   .0131513   .0020632     6.37   0.000     .0091075    .0171951
       3  4  |     .00886    .001645     5.39   0.000     .0056359    .0120842
       3  5  |    .007365   .0015634     4.71   0.000     .0043008    .0104291
       3  6  |   .0050488   .0015237     3.31   0.001     .0020625    .0080352
       3  7  |   .0025505   .0016042     1.59   0.112    -.0005937    .0056947
       3  8  |    .001269   .0016902     0.75   0.453    -.0020437    .0045816
       3  9  |  -.0007448   .0018738    -0.40   0.691    -.0044175    .0029278
       3 10  |  -.0029461   .0021255    -1.39   0.166    -.0071121    .0012198
-------------+----------------------------------------------------------------
1.female_lag |
_predict#_at |
       1  1  |  -.0395993    .008404    -4.71   0.000    -.0560707   -.0231278
       1  2  |   -.036345   .0065041    -5.59   0.000    -.0490928   -.0235972
       1  3  |  -.0343054   .0055704    -6.16   0.000    -.0452232   -.0233875
       1  4  |  -.0315916   .0047309    -6.68   0.000    -.0408639   -.0223193
       1  5  |  -.0305838   .0045587    -6.71   0.000    -.0395188   -.0216489
       1  6  |  -.0289517   .0044534    -6.50   0.000    -.0376803   -.0202231
       1  7  |  -.0270846   .0045831    -5.91   0.000    -.0360673   -.0181019
       1  8  |  -.0260798   .0047478    -5.49   0.000    -.0353852   -.0167744
       1  9  |  -.0244294     .00513    -4.76   0.000     -.034484   -.0143748
       1 10  |  -.0225153   .0056986    -3.95   0.000    -.0336844   -.0113462
       2  1  |   .0177267   .0045446     3.90   0.000     .0088194    .0266339
       2  2  |   .0156778   .0036732     4.27   0.000     .0084785    .0228771
       2  3  |   .0143223   .0032231     4.44   0.000     .0080052    .0206395
       2  4  |    .012445   .0028099     4.43   0.000     .0069378    .0179522
       2  5  |   .0117284   .0027279     4.30   0.000     .0063817     .017075
       2  6  |   .0105471   .0026914     3.92   0.000      .005272    .0158222
       2  7  |   .0091666   .0027974     3.28   0.001     .0036838    .0146495
       2  8  |   .0084116   .0029142     2.89   0.004     .0026998    .0141234
       2  9  |   .0071544   .0031814     2.25   0.025     .0009191    .0133898
       2 10  |   .0056713   .0035821     1.58   0.113    -.0013494     .012692
       3  1  |   .0218726   .0084126     2.60   0.009     .0053842     .038361
       3  2  |   .0206672    .006379     3.24   0.001     .0081646    .0331698
       3  3  |    .019983   .0053897     3.71   0.000     .0094194    .0305466
       3  4  |   .0191466   .0045043     4.25   0.000     .0103183    .0279749
       3  5  |   .0188555   .0043215     4.36   0.000     .0103855    .0273254
       3  6  |   .0184046    .004202     4.38   0.000     .0101689    .0266403
       3  7  |    .017918   .0043123     4.16   0.000     .0094661    .0263698
       3  8  |   .0176682   .0044616     3.96   0.000     .0089236    .0264127
       3  9  |    .017275   .0048077     3.59   0.000     .0078521    .0266978
       3 10  |    .016844   .0053147     3.17   0.002     .0064275    .0272606
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
*** Margins along Job Ladder ***
Students

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))
at           : job_rank_lag    =           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |  -.0122809   .0062152    -1.98   0.048    -.0244625   -.0000993
          2  |   .0044514   .0042144     1.06   0.291    -.0038086    .0127114
          3  |   .0078295   .0060738     1.29   0.197    -.0040749    .0197339
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0323984   .0139395    -2.32   0.020    -.0597194   -.0050775
          2  |   .0087728    .008661     1.01   0.311    -.0082024    .0257481
          3  |   .0236256   .0130163     1.82   0.070    -.0018859     .049137
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
JMC/Postdoc

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))
at           : job_rank_lag    =           2

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |  -.0106049   .0066803    -1.59   0.112    -.0236981    .0024882
          2  |   .0060521   .0047256     1.28   0.200      -.00321    .0153141
          3  |   .0045529   .0065711     0.69   0.488    -.0083262    .0174319
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0315864   .0139841    -2.26   0.024    -.0589947    -.004178
          2  |   .0045914   .0095845     0.48   0.632    -.0141939    .0233768
          3  |   .0269949    .013451     2.01   0.045     .0006314    .0533584
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
Junior Faculty

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))
at           : job_rank_lag    =           3

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   -.009358   .0071642    -1.31   0.191    -.0233996    .0046837
          2  |   .0077951   .0049966     1.56   0.119     -.001998    .0175882
          3  |   .0015629   .0070079     0.22   0.824    -.0121724    .0152981
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0517789   .0145109    -3.57   0.000    -.0802197   -.0233381
          2  |   .0149107   .0102457     1.46   0.146    -.0051705    .0349918
          3  |   .0368682   .0143715     2.57   0.010     .0087006    .0650357
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
Senior Faculty

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))
at           : job_rank_lag    =           4

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |  -.0006191   .0089201    -0.07   0.945    -.0181022    .0168639
          2  |   .0145938   .0060667     2.41   0.016     .0027034    .0264843
          3  |  -.0139747   .0086975    -1.61   0.108    -.0310215    .0030721
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0316942    .016822    -1.88   0.060    -.0646648    .0012764
          2  |    .019616   .0112627     1.74   0.082    -.0024584    .0416905
          3  |   .0120782   .0165041     0.73   0.464    -.0202692    .0444256
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
*** Margins under Different Initial Conditions ***

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))
at           : title_female    =           2
               title_p_acad_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |  -.0067456   .0019537    -3.45   0.001    -.0105748   -.0029164
          2  |   .0013037   .0014055     0.93   0.354     -.001451    .0040583
          3  |   .0054419   .0019473     2.79   0.005     .0016253    .0092586
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0287781   .0051393    -5.60   0.000     -.038851   -.0187051
          2  |     .01056   .0033121     3.19   0.001     .0040684    .0170517
          3  |    .018218   .0049959     3.65   0.000     .0084262    .0280099
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))
at           : title_female    =           1
               title_p_acad_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   -.010451   .0109737    -0.95   0.341     -.031959     .011057
          2  |  -.0006598   .0056555    -0.12   0.907    -.0117443    .0104247
          3  |   .0111108   .0101689     1.09   0.275      -.00882    .0310415
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0276537   .0102555    -2.70   0.007    -.0477541   -.0075533
          2  |   .0274326   .0059218     4.63   0.000     .0158261    .0390392
          3  |   .0002211   .0095828     0.02   0.982    -.0185608    .0190029
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))
at           : title_female    =           0
               title_p_acad_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0014337   .0039772     0.36   0.718    -.0063615     .009229
          2  |   .0007537    .002649     0.28   0.776    -.0044382    .0059456
          3  |  -.0021874   .0038228    -0.57   0.567      -.00968    .0053051
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0414629   .0125078    -3.31   0.001    -.0659778   -.0169481
          2  |   .0152879   .0074079     2.06   0.039     .0007686    .0298072
          3  |    .026175   .0118359     2.21   0.027     .0029771    .0493729
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))
at           : title_female    =           2
               title_person_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |  -.0089172   .0074493    -1.20   0.231    -.0235175    .0056831
          2  |   -.000109   .0036383    -0.03   0.976    -.0072399     .007022
          3  |   .0090261    .007079     1.28   0.202    -.0048484    .0229007
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0226427   .0122368    -1.85   0.064    -.0466264     .001341
          2  |   .0151648   .0058449     2.59   0.009     .0037091    .0266206
          3  |   .0074779   .0113535     0.66   0.510    -.0147746    .0297304
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))
at           : title_female    =           1
               title_person_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |  -.0129773   .0127756    -1.02   0.310    -.0380169    .0120624
          2  |  -.0017613   .0056638    -0.31   0.756    -.0128622    .0093396
          3  |   .0147385   .0120958     1.22   0.223    -.0089689     .038446
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0202516   .0151859    -1.33   0.182    -.0500154    .0095123
          2  |   .0303639   .0075866     4.00   0.000     .0154944    .0452333
          3  |  -.0101123   .0139419    -0.73   0.468     -.037438    .0172134
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    559,786
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==1), predict(pr outcome(1))
2._predict   : Pr(transition==2), predict(pr outcome(2))
3._predict   : Pr(transition==3), predict(pr outcome(3))
at           : title_female    =           0
               title_person_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |  -.0006141   .0083157    -0.07   0.941    -.0169126    .0156844
          2  |  -.0005267   .0041092    -0.13   0.898    -.0085806    .0075272
          3  |   .0011408   .0078987     0.14   0.885    -.0143403    .0166219
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0351412   .0170664    -2.06   0.039    -.0685907   -.0016917
          2  |   .0194937   .0086285     2.26   0.024     .0025822    .0364052
          3  |   .0156475   .0160644     0.97   0.330    -.0158382    .0471332
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
***************************************************************
From Personal

Iteration 0:   log pseudolikelihood = -210799.84  
Iteration 1:   log pseudolikelihood =  -169931.9  
Iteration 2:   log pseudolikelihood = -169278.65  
Iteration 3:   log pseudolikelihood = -169275.09  
Iteration 4:   log pseudolikelihood = -169275.09  

Multinomial logistic regression                 Number of obs     =    196,094
                                                Wald chi2(94)     =   89277.32
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -169275.09               Pseudo R2         =     0.1970

                         (Std. Err. adjusted for 72,194 clusters in title_id1)
------------------------------------------------------------------------------
             |               Robust
  transition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
4            |
  female_lag |
          0  |  -.2665303   .0811859    -3.28   0.001    -.4256516   -.1074089
          1  |  -.6136822   .1005461    -6.10   0.000     -.810749   -.4166154
             |
title_female |
          0  |  -.0348086   .0256828    -1.36   0.175     -.085146    .0155288
          1  |  -.0326639     .03658    -0.89   0.372    -.1043593    .0390315
             |
  female_lag#|
title_female |
        0 0  |   .0519538   .0399753     1.30   0.194    -.0263964     .130304
        0 1  |  -.0327594   .0663997    -0.49   0.622    -.1629004    .0973816
        1 0  |   .1132157    .053488     2.12   0.034     .0083813    .2180502
        1 1  |  -.0138986   .0534328    -0.26   0.795    -.1186249    .0908277
             |
0.title_p_~y |   .0604608   .0195979     3.09   0.002     .0220496    .0988719
             |
  female_lag#|
title_p_ac~y |
        0 0  |  -.0359968   .0344696    -1.04   0.296     -.103556    .0315624
        1 0  |   .1062941   .0443806     2.40   0.017     .0193098    .1932784
             |
1.title_pe~y |  -.0648161   .0238067    -2.72   0.006    -.1114763   -.0181559
             |
  female_lag#|
title_pers~y |
        0 1  |   .0137986   .0448662     0.31   0.758    -.0741375    .1017347
        1 1  |   .0879911   .0449448     1.96   0.050    -.0000992    .1760813
             |
first_female |
          0  |   .0533552   .0203007     2.63   0.009     .0135666    .0931438
          1  |  -.0360873    .030552    -1.18   0.238    -.0959682    .0237936
             |
  female_lag#|
first_female |
        0 0  |  -.0802157   .0361672    -2.22   0.027    -.1511022   -.0093293
        0 1  |   .1183811   .0603039     1.96   0.050     .0001876    .2365747
        1 0  |   .0331154   .0518601     0.64   0.523    -.0685286    .1347594
        1 1  |   .0675648     .05243     1.29   0.198    -.0351961    .1703257
             |
0.first_p_~y |   .4382697   .0224469    19.52   0.000     .3942747    .4822648
             |
  female_lag#|
first_p_ac~y |
        0 0  |   .1921779   .0417771     4.60   0.000     .1102962    .2740596
        1 0  |     .15273   .0537257     2.84   0.004     .0474295    .2580306
             |
1.first_pe~y |  -.2300874   .0219831   -10.47   0.000    -.2731735   -.1870012
             |
  female_lag#|
first_pers~y |
        0 1  |   -.088869   .0428301    -2.07   0.038    -.1728144   -.0049236
        1 1  |   -.001617   .0493992    -0.03   0.974    -.0984377    .0952038
             |
group_p_ac~y |   6.893022   .0573907   120.11   0.000     6.780538    7.005506
             |
  female_lag#|
          c. |
group_p_ac~y |
          0  |   .3782577   .1020625     3.71   0.000      .178219    .5782965
          1  |   1.172692   .1350105     8.69   0.000      .908076    1.437308
             |
group_pers~y |   2.934757   .0698255    42.03   0.000     2.797902    3.071613
             |
  female_lag#|
          c. |
group_pers~y |
          0  |   .2676389   .1256071     2.13   0.033     .0214535    .5138242
          1  |  -.0212353    .141941    -0.15   0.881    -.2994346    .2569639
             |
job_rank_lag |
          1  |  -.0588247    .042322    -1.39   0.165    -.1417743    .0241248
          2  |   -.060281   .0503047    -1.20   0.231    -.1588764    .0383145
          3  |   .0415043   .0526845     0.79   0.431    -.0617553    .1447639
          4  |  -.0182846   .1168437    -0.16   0.876     -.247294    .2107249
             |
  female_lag#|
job_rank_lag |
        0 1  |   .0430502   .0673858     0.64   0.523    -.0890235     .175124
        0 2  |   .1167748   .0820976     1.42   0.155    -.0441335    .2776831
        0 3  |  -.1401535   .0806087    -1.74   0.082    -.2981436    .0178367
        0 4  |   .0809516   .1306575     0.62   0.536    -.1751323    .3370355
        1 1  |  -.0751937   .0890648    -0.84   0.399    -.2497575    .0993701
        1 2  |  -.1258584   .1239348    -1.02   0.310    -.3687662    .1170493
        1 3  |   .0471766   .1044484     0.45   0.652    -.1575385    .2518916
        1 4  |   -.118022   .1857945    -0.64   0.525    -.4821726    .2461285
             |
    ln_post2 |   .1049016   .0084835    12.37   0.000     .0882742     .121529
             |
  female_lag#|
  c.ln_post2 |
          0  |  -.0068286    .014669    -0.47   0.642    -.0355793    .0219221
          1  |   .0090553   .0173153     0.52   0.601    -.0248821    .0429927
             |
       _cons |  -3.763587   .0447462   -84.11   0.000    -3.851288   -3.675886
-------------+----------------------------------------------------------------
5            |
  female_lag |
          0  |  -.4646582   .0886161    -5.24   0.000    -.6383424   -.2909739
          1  |   .1920058   .0922417     2.08   0.037     .0112153    .3727963
             |
title_female |
          0  |  -.0670602   .0263314    -2.55   0.011    -.1186688   -.0154516
          1  |  -.0043854   .0313781    -0.14   0.889    -.0658854    .0571146
             |
  female_lag#|
title_female |
        0 0  |   .1118124   .0427655     2.61   0.009     .0279936    .1956311
        0 1  |   .0660481   .0604559     1.09   0.275    -.0524433    .1845395
        1 0  |   .1234954   .0487416     2.53   0.011     .0279636    .2190271
        1 1  |   .0277899   .0449755     0.62   0.537    -.0603605    .1159402
             |
0.title_p_~y |   .0181516   .0210271     0.86   0.388    -.0230607    .0593639
             |
  female_lag#|
title_p_ac~y |
        0 0  |  -.0288964   .0385665    -0.75   0.454    -.1044853    .0466925
        1 0  |   .0002117   .0427104     0.00   0.996    -.0834992    .0839226
             |
1.title_pe~y |  -.0230529   .0219408    -1.05   0.293    -.0660562    .0199503
             |
  female_lag#|
title_pers~y |
        0 1  |   .0488632   .0432414     1.13   0.258    -.0358884    .1336148
        1 1  |   .0614137   .0383198     1.60   0.109    -.0136918    .1365192
             |
first_female |
          0  |  -.0321579   .0213905    -1.50   0.133    -.0740824    .0097667
          1  |   .0006956   .0276981     0.03   0.980    -.0535917    .0549829
             |
  female_lag#|
first_female |
        0 0  |  -.0098523    .039324    -0.25   0.802    -.0869258    .0672212
        0 1  |   .0480356   .0573135     0.84   0.402    -.0642968    .1603679
        1 0  |   .0314334   .0473234     0.66   0.507    -.0613188    .1241855
        1 1  |  -.0068072   .0450933    -0.15   0.880    -.0951885     .081574
             |
0.first_p_~y |   .2264738   .0242625     9.33   0.000     .1789201    .2740274
             |
  female_lag#|
first_p_ac~y |
        0 0  |   .0898833    .046559     1.93   0.054    -.0013707    .1811372
        1 0  |  -.0092339   .0510273    -0.18   0.856    -.1092455    .0907777
             |
1.first_pe~y |  -.5036074   .0224326   -22.45   0.000    -.5475744   -.4596403
             |
  female_lag#|
first_pers~y |
        0 1  |  -.0541941   .0450397    -1.20   0.229    -.1424704    .0340822
        1 1  |   .0779522   .0428787     1.82   0.069    -.0060884    .1619929
             |
group_p_ac~y |   3.084752   .0643188    47.96   0.000      2.95869    3.210815
             |
  female_lag#|
          c. |
group_p_ac~y |
          0  |   .3451482   .1165978     2.96   0.003     .1166207    .5736758
          1  |  -.1800528   .1354054    -1.33   0.184    -.4454426    .0853369
             |
group_pers~y |   7.259072   .0649638   111.74   0.000     7.131745    7.386399
             |
  female_lag#|
          c. |
group_pers~y |
          0  |   .4192538   .1228667     3.41   0.001     .1784395    .6600682
          1  |  -.6802368   .1187063    -5.73   0.000    -.9128969   -.4475767
             |
job_rank_lag |
          1  |   .0278151   .0493131     0.56   0.573    -.0688368    .1244671
          2  |  -.0621305   .0623741    -1.00   0.319    -.1843814    .0601204
          3  |   .1360186   .0631042     2.16   0.031     .0123366    .2597007
          4  |  -.1687442   .1530869    -1.10   0.270     -.468789    .1313006
             |
  female_lag#|
job_rank_lag |
        0 1  |  -.0822459   .0802747    -1.02   0.306    -.2395814    .0750896
        0 2  |    .210551   .1028489     2.05   0.041     .0089708    .4121311
        0 3  |  -.0987256   .0955231    -1.03   0.301    -.2859475    .0884963
        0 4  |   .1973672   .1707879     1.16   0.248    -.1373709    .5321054
        1 1  |  -.0676277   .0879782    -0.77   0.442    -.2400618    .1048064
        1 2  |  -.0231388   .1279445    -0.18   0.856    -.2739055    .2276279
        1 3  |  -.0536612   .1135266    -0.47   0.636    -.2761693    .1688468
        1 4  |   -.137036   .2226403    -0.62   0.538    -.5734029    .2993309
             |
    ln_post2 |   .2734416   .0092412    29.59   0.000     .2553291     .291554
             |
  female_lag#|
  c.ln_post2 |
          0  |   .0629753   .0163026     3.86   0.000     .0310227    .0949278
          1  |   .0141393   .0160878     0.88   0.379    -.0173922    .0456708
             |
       _cons |  -4.184894    .048143   -86.93   0.000    -4.279253   -4.090536
-------------+----------------------------------------------------------------
6            |  (base outcome)
------------------------------------------------------------------------------
average ME

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0014794   .0023448     0.63   0.528    -.0031162     .006075
          2  |  -.0058612   .0023054    -2.54   0.011    -.0103797   -.0013426
          3  |   .0043818   .0026189     1.67   0.094    -.0007511    .0095146
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0034268   .0031693     1.08   0.280    -.0027848    .0096385
          2  |   -.001269    .002628    -0.48   0.629    -.0064198    .0038819
          3  |  -.0021579   .0032253    -0.67   0.503    -.0084793    .0041635
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
*** Margins along Job Ladder ***
Students

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))
at           : job_rank_lag    =           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |    .013042   .0097118     1.34   0.179    -.0059927    .0320767
          2  |  -.0205214   .0105055    -1.95   0.051    -.0411118     .000069
          3  |   .0074794   .0117994     0.63   0.526    -.0156469    .0306057
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0028907   .0125798    -0.23   0.818    -.0275466    .0217652
          2  |  -.0070533   .0123573    -0.57   0.568    -.0312731    .0171665
          3  |   .0099439   .0139975     0.71   0.477    -.0174906    .0373785
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
JMC/Postdoc

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))
at           : job_rank_lag    =           2

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0077831   .0120846     0.64   0.520    -.0159023    .0314685
          2  |   .0184709   .0139992     1.32   0.187     -.008967    .0459087
          3  |   -.026254   .0147607    -1.78   0.075    -.0551845    .0026765
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0133424   .0172728    -0.77   0.440    -.0471964    .0205115
          2  |   .0023134   .0176288     0.13   0.896    -.0322384    .0368653
          3  |    .011029   .0202373     0.54   0.586    -.0286355    .0506935
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
Junior Faculty

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))
at           : job_rank_lag    =           3

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   -.015461   .0116538    -1.33   0.185    -.0383019      .00738
          2  |  -.0129614   .0131222    -0.99   0.323    -.0386804    .0127576
          3  |   .0284224    .014157     2.01   0.045     .0006752    .0561695
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0147301   .0150717     0.98   0.328    -.0148098      .04427
          2  |  -.0117263   .0159515    -0.74   0.462    -.0429906     .019538
          3  |  -.0030038   .0172767    -0.17   0.862    -.0368656    .0308579
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
Senior Faculty

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))
at           : job_rank_lag    =           4

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0031686   .0199978     0.16   0.874    -.0360264    .0423636
          2  |   .0180775   .0222981     0.81   0.418     -.025626    .0617809
          3  |  -.0212461   .0242061    -0.88   0.380    -.0686892     .026197
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0075363    .027378    -0.28   0.783    -.0611962    .0461236
          2  |  -.0142017   .0286195    -0.50   0.620    -.0702948    .0418914
          3  |    .021738   .0326908     0.66   0.506    -.0423347    .0858107
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
*** Margins under Different Initial Conditions ***

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))
at           : title_female    =           2
               title_p_acad_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0042612   .0037513     1.14   0.256    -.0030913    .0116137
          2  |  -.0075367   .0043357    -1.74   0.082    -.0160345     .000961
          3  |   .0032755   .0046613     0.70   0.482    -.0058605    .0124114
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0059625   .0047865    -1.25   0.213    -.0153438    .0034189
          2  |  -.0005597    .005027    -0.11   0.911    -.0104125    .0092931
          3  |   .0065221   .0056947     1.15   0.252    -.0046392    .0176835
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))
at           : title_female    =           1
               title_p_acad_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   -.004867   .0101131    -0.48   0.630    -.0246882    .0149543
          2  |   .0041329   .0087748     0.47   0.638    -.0130653    .0213311
          3  |   .0007341   .0102386     0.07   0.943    -.0193331    .0208014
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0091207   .0082969    -1.10   0.272    -.0253823    .0071409
          2  |   .0043109   .0073674     0.59   0.558    -.0101288    .0187507
          3  |   .0048098   .0087456     0.55   0.582    -.0123313    .0219508
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))
at           : title_female    =           0
               title_p_acad_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0062486   .0064705     0.97   0.334    -.0064332    .0189305
          2  |   .0059842   .0065579     0.91   0.361     -.006869    .0188375
          3  |  -.0122329    .007357    -1.66   0.096    -.0266523    .0021865
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0045716   .0082451     0.55   0.579    -.0115885    .0207318
          2  |   .0116783   .0077628     1.50   0.132    -.0035365    .0268932
          3  |    -.01625   .0089421    -1.82   0.069    -.0337762    .0012762
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))
at           : title_female    =           2
               title_person_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0017523    .006296     0.28   0.781    -.0105876    .0140922
          2  |  -.0047378   .0051256    -0.92   0.355    -.0147839    .0053083
          3  |   .0029855   .0064875     0.46   0.645    -.0097297    .0157007
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0113008   .0064691     1.75   0.081    -.0013784      .02398
          2  |  -.0009541   .0049329    -0.19   0.847    -.0106224    .0087143
          3  |  -.0103467   .0063531    -1.63   0.103    -.0227985     .002105
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))
at           : title_female    =           1
               title_person_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |  -.0073665   .0109526    -0.67   0.501    -.0288333    .0141002
          2  |    .007083   .0089762     0.79   0.430      -.01051     .024676
          3  |   .0002835   .0107725     0.03   0.979    -.0208303    .0213973
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0078211   .0091095     0.86   0.391    -.0100332    .0256754
          2  |   .0040809   .0070303     0.58   0.562    -.0096982    .0178601
          3  |   -.011902   .0088603    -1.34   0.179     -.029268    .0054639
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    196,094
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==4), predict(pr outcome(4))
2._predict   : Pr(transition==5), predict(pr outcome(5))
3._predict   : Pr(transition==6), predict(pr outcome(6))
at           : title_female    =           0
               title_person_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0037305   .0081296     0.46   0.646    -.0122033    .0196643
          2  |   .0088778   .0071158     1.25   0.212    -.0050688    .0228245
          3  |  -.0126084   .0085485    -1.47   0.140    -.0293631    .0041464
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0221083   .0095067     2.33   0.020     .0034756     .040741
          2  |   .0110605   .0076716     1.44   0.149    -.0039755    .0260965
          3  |  -.0331688   .0092998    -3.57   0.000    -.0513961   -.0149415
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
***************************************************************
From Others

Iteration 0:   log pseudolikelihood = -543643.56  
Iteration 1:   log pseudolikelihood = -441362.82  
Iteration 2:   log pseudolikelihood = -434336.98  
Iteration 3:   log pseudolikelihood = -434244.31  
Iteration 4:   log pseudolikelihood = -434244.22  
Iteration 5:   log pseudolikelihood = -434244.22  

Multinomial logistic regression                 Number of obs     =    557,181
                                                Wald chi2(94)     =  234286.07
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -434244.22               Pseudo R2         =     0.2012

                        (Std. Err. adjusted for 106,063 clusters in title_id1)
------------------------------------------------------------------------------
             |               Robust
  transition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
7            |
  female_lag |
          0  |   .0079458   .0428284     0.19   0.853    -.0759962    .0918879
          1  |  -.3661756   .0914095    -4.01   0.000    -.5453349   -.1870163
             |
title_female |
          0  |  -.0035221   .0100951    -0.35   0.727    -.0233082    .0162639
          1  |  -.0617838   .0172185    -3.59   0.000    -.0955314   -.0280363
             |
  female_lag#|
title_female |
        0 0  |   .0343683   .0240444     1.43   0.153    -.0127579    .0814945
        0 1  |  -.0445337    .053108    -0.84   0.402    -.1486236    .0595562
        1 0  |  -.0106247   .0654796    -0.16   0.871    -.1389624     .117713
        1 1  |   .0855818   .0464265     1.84   0.065    -.0054124    .1765761
             |
0.title_p_~y |   .0424191   .0074405     5.70   0.000     .0278359    .0570023
             |
  female_lag#|
title_p_ac~y |
        0 0  |   .0002382   .0216689     0.01   0.991    -.0422319    .0427084
        1 0  |  -.0064851   .0455599    -0.14   0.887    -.0957807    .0828106
             |
1.title_pe~y |  -.0391752   .0128257    -3.05   0.002    -.0643132   -.0140373
             |
  female_lag#|
title_pers~y |
        0 1  |   .0054785   .0384451     0.14   0.887    -.0698724    .0808295
        1 1  |   .0008047   .0523074     0.02   0.988    -.1017158    .1033252
             |
first_female |
          0  |   .0266646   .0083407     3.20   0.001     .0103171    .0430121
          1  |   .0193514   .0145599     1.33   0.184    -.0091855    .0478884
             |
  female_lag#|
first_female |
        0 0  |  -.0790723   .0215596    -3.67   0.000    -.1213284   -.0368162
        0 1  |  -.1115724   .0460222    -2.42   0.015    -.2017743   -.0213705
        1 0  |  -.0541478   .0545917    -0.99   0.321    -.1611455      .05285
        1 1  |  -.0800249   .0472364    -1.69   0.090    -.1726065    .0125567
             |
0.first_p_~y |   .3946698    .008314    47.47   0.000     .3783747    .4109648
             |
  female_lag#|
first_p_ac~y |
        0 0  |   .0299719    .023732     1.26   0.207    -.0165419    .0764858
        1 0  |   .1697852   .0518834     3.27   0.001     .0680957    .2714748
             |
1.first_pe~y |  -.0924526    .010609    -8.71   0.000    -.1132458   -.0716594
             |
  female_lag#|
first_pers~y |
        0 1  |   .0310127   .0309552     1.00   0.316    -.0296584    .0916839
        1 1  |   .0482565   .0512195     0.94   0.346    -.0521319     .148645
             |
group_p_ac~y |    6.33625   .0222052   285.35   0.000     6.292729    6.379772
             |
  female_lag#|
          c. |
group_p_ac~y |
          0  |   .2287348   .0622488     3.67   0.000     .1067294    .3507402
          1  |   1.050826   .1351436     7.78   0.000     .7859498    1.315703
             |
group_pers~y |   2.384812    .036963    64.52   0.000     2.312365    2.457258
             |
  female_lag#|
          c. |
group_pers~y |
          0  |   -.136234   .1078955    -1.26   0.207    -.3477053    .0752373
          1  |  -.2743569   .1683071    -1.63   0.103    -.6042328    .0555189
             |
job_rank_lag |
          1  |   .0319079   .1407653     0.23   0.821    -.2439871    .3078029
          2  |  -.2418315   .1197954    -2.02   0.044    -.4766262   -.0070368
          3  |  -.0858122   .1972479    -0.44   0.664    -.4724109    .3007865
          4  |  -.4378053    .245743    -1.78   0.075    -.9194526    .0438421
             |
  female_lag#|
job_rank_lag |
        0 1  |   .1112867   .2171805     0.51   0.608    -.3143792    .5369526
        0 2  |  -.0503639   .1777967    -0.28   0.777    -.3988392    .2981113
        0 3  |  -.0713126   .2167695    -0.33   0.742     -.496173    .3535479
        0 4  |   .3333239   .2495454     1.34   0.182    -.1557761    .8224238
        1 1  |     -.7835   .7306578    -1.07   0.284    -2.215563    .6485629
        1 2  |  -.0713544   .2676204    -0.27   0.790    -.5958807    .4531718
        1 3  |  -.4451764   .3300863    -1.35   0.177    -1.092134    .2017809
        1 4  |    .252223   .2730174     0.92   0.356    -.2828812    .7873273
             |
    ln_post2 |   .0461019   .0039184    11.77   0.000     .0384219    .0537818
             |
  female_lag#|
  c.ln_post2 |
          0  |  -.0144372   .0100388    -1.44   0.150    -.0341129    .0052386
          1  |  -.0118508   .0207014    -0.57   0.567    -.0524249    .0287232
             |
       _cons |  -3.283316   .0154261  -212.84   0.000    -3.313551   -3.253081
-------------+----------------------------------------------------------------
8            |
  female_lag |
          0  |   .0438986   .0604043     0.73   0.467    -.0744916    .1622889
          1  |   .5018338    .094435     5.31   0.000     .3167447     .686923
             |
title_female |
          0  |  -.0092741   .0137975    -0.67   0.501    -.0363167    .0177686
          1  |  -.0025234   .0187579    -0.13   0.893    -.0392881    .0342413
             |
  female_lag#|
title_female |
        0 0  |   .0318507    .032665     0.98   0.330    -.0321714    .0958729
        0 1  |   -.066948   .0535248    -1.25   0.211    -.1718547    .0379588
        1 0  |   .0349675   .0617685     0.57   0.571    -.0860965    .1560316
        1 1  |   .0055226    .044784     0.12   0.902    -.0822525    .0932977
             |
0.title_p_~y |   .0388495   .0106403     3.65   0.000     .0179948    .0597041
             |
  female_lag#|
title_p_ac~y |
        0 0  |  -.0029929   .0300161    -0.10   0.921    -.0618234    .0558377
        1 0  |   .0176386   .0492186     0.36   0.720     -.078828    .1141052
             |
1.title_pe~y |  -.1586032   .0150066   -10.57   0.000    -.1880156   -.1291908
             |
  female_lag#|
title_pers~y |
        0 1  |   -.063876   .0424744    -1.50   0.133    -.1471244    .0193724
        1 1  |   .1419747   .0465753     3.05   0.002     .0506888    .2332605
             |
first_female |
          0  |   .0144527   .0119248     1.21   0.226    -.0089195    .0378248
          1  |  -.0633399   .0179409    -3.53   0.000    -.0985034   -.0281764
             |
  female_lag#|
first_female |
        0 0  |  -.0482006   .0292498    -1.65   0.099    -.1055291    .0091279
        0 1  |  -.0571394   .0527623    -1.08   0.279    -.1605517    .0462729
        1 0  |  -.0547684   .0552488    -0.99   0.322    -.1630541    .0535173
        1 1  |   .0276047   .0464734     0.59   0.553    -.0634814    .1186908
             |
0.first_p_~y |   .1619302   .0119988    13.50   0.000     .1384129    .1854474
             |
  female_lag#|
first_p_ac~y |
        0 0  |  -.0451323   .0336732    -1.34   0.180    -.1111306    .0208659
        1 0  |   .0242125   .0545228     0.44   0.657    -.0826502    .1310752
             |
1.first_pe~y |  -.6272854    .013967   -44.91   0.000    -.6546602   -.5999106
             |
  female_lag#|
first_pers~y |
        0 1  |  -.1163121   .0386639    -3.01   0.003    -.1920919   -.0405323
        1 1  |   .1153087   .0481878     2.39   0.017     .0208623    .2097551
             |
group_p_ac~y |   2.415548    .033044    73.10   0.000     2.350782    2.480313
             |
  female_lag#|
          c. |
group_p_ac~y |
          0  |   .0991443   .0935812     1.06   0.289    -.0842714      .28256
          1  |   .0756418   .1582292     0.48   0.633    -.2344817    .3857653
             |
group_pers~y |   9.288035   .0440989   210.62   0.000     9.201603    9.374467
             |
  female_lag#|
          c. |
group_pers~y |
          0  |   .4023023   .1148757     3.50   0.000       .17715    .6274547
          1  |  -1.952765   .1440316   -13.56   0.000    -2.235062   -1.670469
             |
job_rank_lag |
          1  |    .127059   .1992025     0.64   0.524    -.2633707    .5174887
          2  |  -.3862286   .2282848    -1.69   0.091    -.8336586    .0612015
          3  |   .1624853   .2953138     0.55   0.582    -.4163191    .7412897
          4  |  -.1873537   .3723418    -0.50   0.615    -.9171302    .5424227
             |
  female_lag#|
job_rank_lag |
        0 1  |  -.3539654   .3426119    -1.03   0.302    -1.025472    .3175416
        0 2  |   .4157875   .2970967     1.40   0.162    -.1665114    .9980863
        0 3  |  -.1704351   .3241749    -0.53   0.599    -.8058062    .4649361
        0 4  |   .1219224   .3772044     0.32   0.747    -.6173845    .8612294
        1 1  |   .0846999    .561098     0.15   0.880    -1.015032    1.184432
        1 2  |   .2586614   .3908943     0.66   0.508    -.5074773      1.0248
        1 3  |  -.2299863   .4326912    -0.53   0.595    -1.078045    .6180729
        1 4  |  -.1382989   .4093409    -0.34   0.735    -.9405923    .6639946
             |
    ln_post2 |   .1314413   .0051707    25.42   0.000      .121307    .1415755
             |
  female_lag#|
  c.ln_post2 |
          0  |  -.0179476   .0133465    -1.34   0.179    -.0441063    .0082111
          1  |  -.0364446   .0200951    -1.81   0.070    -.0758304    .0029411
             |
       _cons |  -3.864179   .0221053  -174.81   0.000    -3.907504   -3.820853
-------------+----------------------------------------------------------------
9            |  (base outcome)
------------------------------------------------------------------------------
average ME

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0071987   .0016626     4.33   0.000     .0039401    .0104572
          2  |   .0013612   .0012684     1.07   0.283    -.0011248    .0038471
          3  |  -.0085599    .001784    -4.80   0.000    -.0120565   -.0050633
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0046205   .0038168     1.21   0.226    -.0028603    .0121014
          2  |   .0108533   .0024598     4.41   0.000     .0060321    .0156745
          3  |  -.0154738   .0038312    -4.04   0.000    -.0229829   -.0079648
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
*** Margins along Job Ladder ***
Students

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))
at           : job_rank_lag    =           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0372659   .0358994     1.04   0.299    -.0330957    .1076276
          2  |  -.0344696   .0293088    -1.18   0.240    -.0919138    .0229745
          3  |  -.0027963   .0392743    -0.07   0.943    -.0797724    .0741798
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.1118952   .0981053    -1.14   0.254    -.3041781    .0803876
          2  |   .0528034   .0821778     0.64   0.521    -.1082621    .2138688
          3  |   .0590918    .083463     0.71   0.479    -.1044925    .2226762
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
JMC/Postdoc

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))
at           : job_rank_lag    =           2

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |  -.0125501   .0269834    -0.47   0.642    -.0654366    .0403363
          2  |   .0406665   .0257786     1.58   0.115    -.0098586    .0911916
          3  |  -.0281164   .0328629    -0.86   0.392    -.0925265    .0362937
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0105662   .0393053    -0.27   0.788    -.0876031    .0664707
          2  |   .0347324   .0376758     0.92   0.357    -.0391109    .1085756
          3  |  -.0241662   .0460685    -0.52   0.600    -.1144588    .0661264
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
Junior Faculty

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))
at           : job_rank_lag    =           3

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0011911   .0337971     0.04   0.972      -.06505    .0674321
          2  |  -.0135191    .032494    -0.42   0.677    -.0772061     .050168
          3  |    .012328   .0400911     0.31   0.758    -.0662492    .0909052
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0524847    .046945    -1.12   0.264    -.1444952    .0395259
          2  |   .0021948   .0462598     0.05   0.962    -.0884728    .0928625
          3  |   .0502898   .0568424     0.88   0.376    -.0611193    .1616989
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
Senior Faculty

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))
at           : job_rank_lag    =           4

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0559123   .0359442     1.56   0.120    -.0145371    .1263617
          2  |   .0031779   .0337466     0.09   0.925    -.0629642    .0693201
          3  |  -.0590902   .0453891    -1.30   0.193    -.1480512    .0298707
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |    .050347   .0392098     1.28   0.199    -.0265028    .1271968
          2  |  -.0111581    .036486    -0.31   0.760    -.0826694    .0603532
          3  |  -.0391889   .0493871    -0.79   0.427    -.1359859    .0576081
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
*** Margins under Different Initial Conditions ***

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))
at           : title_female    =           2
               title_p_acad_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0067157   .0025086     2.68   0.007     .0017988    .0116325
          2  |   .0018161   .0022485     0.81   0.419    -.0025908    .0062229
          3  |  -.0085317   .0029174    -2.92   0.003    -.0142497   -.0028138
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0054081   .0055278     0.98   0.328    -.0054263    .0162424
          2  |   .0088226   .0043341     2.04   0.042     .0003279    .0173173
          3  |  -.0142307   .0060739    -2.34   0.019    -.0261352   -.0023261
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))
at           : title_female    =           1
               title_p_acad_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0017053   .0083612     0.20   0.838    -.0146824     .018093
          2  |  -.0030466   .0049547    -0.61   0.539    -.0127577    .0066645
          3  |   .0013413   .0083819     0.16   0.873    -.0150869    .0177695
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0191907   .0081154     2.36   0.018     .0032849    .0350965
          2  |   .0065162   .0055037     1.18   0.236     -.004271    .0173033
          3  |  -.0257069   .0083452    -3.08   0.002    -.0420632   -.0093506
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))
at           : title_female    =           0
               title_p_acad_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0113522   .0040974     2.77   0.006     .0033215    .0193828
          2  |    .003679   .0033828     1.09   0.277    -.0029512    .0103093
          3  |  -.0150312   .0045324    -3.32   0.001    -.0239145   -.0061479
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0025459   .0105008     0.24   0.808    -.0180353    .0231272
          2  |   .0128461   .0070382     1.83   0.068    -.0009486    .0266408
          3  |   -.015392   .0108789    -1.41   0.157    -.0367142    .0059302
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))
at           : title_female    =           2
               title_person_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |   .0093808   .0060421     1.55   0.121    -.0024615     .021223
          2  |  -.0031063   .0032572    -0.95   0.340    -.0094903    .0032777
          3  |  -.0062745    .006083    -1.03   0.302    -.0181969     .005648
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0009254   .0083123     0.11   0.911    -.0153665    .0172173
          2  |   .0211939   .0048015     4.41   0.000     .0117831    .0306047
          3  |  -.0221193   .0081833    -2.70   0.007    -.0381583   -.0060803
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))
at           : title_female    =           1
               title_person_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |    .004054   .0094906     0.43   0.669    -.0145473    .0226553
          2  |  -.0075807   .0049455    -1.53   0.125    -.0172737    .0021123
          3  |   .0035267     .00947     0.37   0.710    -.0150342    .0220876
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |   .0147577   .0098134     1.50   0.133    -.0044763    .0339916
          2  |   .0190187   .0056562     3.36   0.001     .0079327    .0301047
          3  |  -.0337763   .0095555    -3.53   0.000    -.0525049   -.0150478
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

Average marginal effects                        Number of obs     =    557,181
Model VCE    : Robust

dy/dx w.r.t. : 0.female_lag 1.female_lag
1._predict   : Pr(transition==7), predict(pr outcome(7))
2._predict   : Pr(transition==8), predict(pr outcome(8))
3._predict   : Pr(transition==9), predict(pr outcome(9))
at           : title_female    =           0
               title_person_dummy=           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.female_lag |
    _predict |
          1  |    .014161    .006792     2.08   0.037      .000849     .027473
          2  |  -.0013838   .0039557    -0.35   0.726    -.0091369    .0063693
          3  |  -.0127772   .0069127    -1.85   0.065    -.0263258    .0007714
-------------+----------------------------------------------------------------
1.female_lag |
    _predict |
          1  |  -.0019162   .0122494    -0.16   0.876    -.0259246    .0220923
          2  |   .0252142   .0072968     3.46   0.001     .0109127    .0395157
          3  |  -.0232981   .0122973    -1.89   0.058    -.0474003    .0008042
-------------+----------------------------------------------------------------
2.female_lag |  (base outcome)
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. log close
      name:  <unnamed>
       log:  /accounts/grad/haowen.wu/Documents/EJR-revise/dynamic/check_May201
> 9/mlogit-full-before-Aug2017.log
  log type:  text
 closed on:  26 May 2019, 07:15:32
-------------------------------------------------------------------------------
